The increasing amount of data which is measured in processes of many different branches is often not sufficiently exploited. Moreover, the increasing abilities concerning data collection are often not met by appropriate capabilities of making use thereof. Consequently, more emphasis should be put on the development of evaluation techniques, which allow to convert raw data into more meaningful information. In this article, a concept is introduced which automatically extracts regularities of a process series that indicate an unsuccessful outcome. These regularities are expressed in rules such as those used in expert systems.
|Translated title of the contribution||A method for an automated rule extraction from raw process data Part 1: Process trends, wavelet transformation and decision trees|
|Number of pages||10|
|State||Published - Feb 1996|
ASJC Scopus subject areas
- Control and Systems Engineering
- Computer Science Applications
- Electrical and Electronic Engineering